Agencies want to take advantage of location data, but roadblocks still stand in the way.

For Mobext, the mobile arm of Havas Media Group, fragmentation and quality-control issues top the list.

“A lot of companies have hopped on the bandwagon in the location space, and that’s created a lot of clutter in the offerings available out there,” said Patricia Lopez, head of Mobext in the UK. “There also aren’t a lot of standardized tools to verify the quality of those offerings.”

Mobext has worked with several location data and service providers, including xAd and Factual.

Most recently, it’s been experimenting with Adsquare, a mobile data exchange that’s starting to aggregate location and sensor data from providers under one roof for use in segmentation and mobile programmatic buying.

Tapping into both types of data provides a check on quality without losing scale, said Adsquare CEO and co-founder Tom Laband. Exchange-level impression data delivers the scale, while companies with access to beacon and proximity data provide a truth set to keep the demand-side and supply-side platforms honest.

“We’re looking to provide scale for first-party proximity data, and from there to improve the segmentation and distribution of location and proximity data available in the market,” Laband said.

Mobext uses Adsquare to dip its toe into location-based targeting for clients such as Kia, which recently approached the agency to find auto intenders who had visited a dealership within the past few weeks. In another case, Mobext was able to pull together an audience of people who frequent high-end retail stores for a luxury client.

Marketers are starting to see the value in using visitation to build segments, but Mobext says education is still needed.

“To us, location is like a real-life cookie,” Lopez said. “Rather than asking us to find females between 18 and 24, we want clients to ask questions like, ‘Where do females between 18 and 24 actually go in the real world?’”

As marketers get more sophisticated, they’re going to start looking for more customized segments based on location. This may include males in their 20s who visited a McDonald’s in the last 24 hours, for example, rather than off-the-shelf segments of business travelers, Starbucks-visiting “coffee lovers” or “bargain hunters” who spend time at Walmart.

“When you get so granular, it can get tricky in terms of reach,” Laband said. “That’s why it makes sense to aggregate data, to combine location data and proximity data with other parameters, like psychographics and demographics, into one mobile data marketplace.”

It’s still early days on that front. Although the use cases for proximity data derived from beacons go beyond audience buying and retargeting to more sophisticated methods, including data modeling, attribution and verification, brands aren’t really taking advantage yet.

“Most location data is commoditized, in the sense that the market is trading on the same data with their products layered on top,” said Unacast CRO Chris Cunningham. “[But] we are in the middle of a learning curve in the market in appreciating that proximity data can solve for other core business objectives and pain points.”